Strong consistency of M-estimates in linear models
โ Scribed by Zhao Lincheng
- Publisher
- SP Science China Press
- Year
- 2002
- Tongue
- English
- Weight
- 139 KB
- Volume
- 45
- Category
- Article
- ISSN
- 1674-7283
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Under minimum assumptions on the stochastic regressors, strong consistency of Bayes estimates is established in stochastic regression models in two cases: (1) When the prior distribution is discrete, the p.d.f. f of i.i.d. random errors is assumed to have finite Fisher information I= & ( f $) 2 รf
A broad range of nonlinear (linear) time series and stochastic processes can be described by the stochastic regression model y. = r.(O)+ e., where {en} are independent random disturbances and r. is a random function of an unknown parameter 0 measurable with respect to the a-field ~r(yl ..... y.-l).